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10.1186/s12864-016-3057-8 http://scihub22266oqcxt.onion/10.1186/s12864-016-3057-8 C5016927!5016927 !27612452     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=27612452 &cmd=llinks): Failed to open stream: HTTP request failed! 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Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration |pdf=|usr=}}{{27612452 }} gab.com Text Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration JO: BMC Genomics http://www.kidney.de/pget.php?&tw=1&pmid=27612452 #FOAvip BACKGROUND: Human diseases are commonly the result of multidimensional changes at molecular, cellular, and systemic levels. Recent advances in genomic technologies have enabled an outpour of omics datasets that capture these changes. However, separate analyses of these various data only provide fragmented understanding and do not capture the holistic view of disease mechanisms. To meet the urgent needs for tools that effectively integrate multiple types of omics data to derive biological insights, we have developed Mergeomics, a computational pipeline that integrates multidimensional disease association data with functional genomics and molecular networks to retrieve biological pathways, gene networks, and central regulators critical for disease development. RESULTS: To make the Mergeomics pipeline available to a wider research community, we have implemented an online, user-friendly web server ( http://mergeomics. RESEARCH: idre.ucla.edu/ ). The web server features a modular implementation of the Mergeomics pipeline with detailed tutorials. Additionally, it provides curated genomic resources including tissue-specific expression quantitative trait loci, ENCODE functional annotations, biological pathways, and molecular networks, and offers interactive visualization of analytical results. Multiple computational tools including Marker Dependency Filtering (MDF), Marker Set Enrichment Analysis (MSEA), Meta-MSEA, and Weighted Key Driver Analysis (wKDA) can be used separately or in flexible combinations. User-defined summary-level genomic association datasets (e.g., genetic, transcriptomic, epigenomic) related to a particular disease or phenotype can be uploaded and computed real-time to yield biologically interpretable results, which can be viewed online and downloaded for later use. CONCLUSIONS: Our Mergeomics web server offers researchers flexible and user-friendly tools to facilitate integration of multidimensional data into holistic views of disease mechanisms in the form of tissue-specific key regulators, biological pathways, and gene networks. Twit Text FOAVip Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration ????BMC Genomics http://www.kidney.de/pget.php?&tw=1&pmid=27612452 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27612452 #FOAvip English Wikipedia <ref>{{Cite pmid|27612452 }}</ref> Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration #MMPMID27612452 Arneson D ; Bhattacharya A ; Shu L ; Mäkinen VP ; Yang X BMC Genomics 2016[Sep]; 17 (1 ): 722 PMID27612452 show ga BACKGROUND: Human diseases are commonly the result of multidimensional changes at molecular, cellular, and systemic levels. Recent advances in genomic technologies have enabled an outpour of omics datasets that capture these changes. However, separate analyses of these various data only provide fragmented understanding and do not capture the holistic view of disease mechanisms. To meet the urgent needs for tools that effectively integrate multiple types of omics data to derive biological insights, we have developed Mergeomics, a computational pipeline that integrates multidimensional disease association data with functional genomics and molecular networks to retrieve biological pathways, gene networks, and central regulators critical for disease development. RESULTS: To make the Mergeomics pipeline available to a wider research community, we have implemented an online, user-friendly web server ( http://mergeomics. RESEARCH: idre.ucla.edu/ ). The web server features a modular implementation of the Mergeomics pipeline with detailed tutorials. Additionally, it provides curated genomic resources including tissue-specific expression quantitative trait loci, ENCODE functional annotations, biological pathways, and molecular networks, and offers interactive visualization of analytical results. Multiple computational tools including Marker Dependency Filtering (MDF), Marker Set Enrichment Analysis (MSEA), Meta-MSEA, and Weighted Key Driver Analysis (wKDA) can be used separately or in flexible combinations. User-defined summary-level genomic association datasets (e.g., genetic, transcriptomic, epigenomic) related to a particular disease or phenotype can be uploaded and computed real-time to yield biologically interpretable results, which can be viewed online and downloaded for later use. CONCLUSIONS: Our Mergeomics web server offers researchers flexible and user-friendly tools to facilitate integration of multidimensional data into holistic views of disease mechanisms in the form of tissue-specific key regulators, biological pathways, and gene networks. |*Software [MESH] |*Web Browser [MESH] |Disease Susceptibility [MESH] |Gene Regulatory Networks [MESH] |Genetic Association Studies [MESH] |Genomics/*methods [MESH] |Humans [MESH] |Signal Transduction [MESH]Mergeomics: a web server for identifying pathological pathways, networ(epmc).pdf DeepDyve Pubget Overpricing